Nonlinear conjugate gradient methods: worst-case convergence rates via computer-assisted analyses
Fuente:
arXiv
Saved in:
| Main Authors: | Gupta, Shuvomoy Das, Freund, Robert M., Sun, Xu Andy, Taylor, Adrien |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
The AutoLyap software suite for computer-assisted Lyapunov analyses of first-order methods
by: Upadhyaya, Manu, et al.
Published: (2025)
by: Upadhyaya, Manu, et al.
Published: (2025)
PEPit: computer-assisted worst-case analyses of first-order optimization methods in Python
by: Goujaud, Baptiste, et al.
Published: (2022)
by: Goujaud, Baptiste, et al.
Published: (2022)
Exact worst-case convergence rates for Douglas--Rachford and Davis--Yin splitting methods
by: Nguyen, Edward Duc Hien, et al.
Published: (2025)
by: Nguyen, Edward Duc Hien, et al.
Published: (2025)
Exact worst-case convergence rates of gradient descent: a complete analysis for all constant stepsizes over nonconvex and convex functions
by: Rotaru, Teodor, et al.
Published: (2024)
by: Rotaru, Teodor, et al.
Published: (2024)
Computer-Assisted Design of Accelerated Composite Optimization Methods: OptISTA
by: Jang, Uijeong, et al.
Published: (2023)
by: Jang, Uijeong, et al.
Published: (2023)
Analytic analysis of the worst-case complexity of the gradient method with exact line search and the Polyak stepsize
by: Huang, Ya-Kui, et al.
Published: (2024)
by: Huang, Ya-Kui, et al.
Published: (2024)
On the convergence rate of the boosted Difference-of-Convex Algorithm (DCA)
by: Abbaszadehpeivasti, Hadi, et al.
Published: (2025)
by: Abbaszadehpeivasti, Hadi, et al.
Published: (2025)
Lower and upper bounds of the convergence rate of gradient methods with composite noise in gradient
by: Vasin, Artem, et al.
Published: (2026)
by: Vasin, Artem, et al.
Published: (2026)
Exterior-point Optimization for Sparse and Low-rank Optimization
by: Gupta, Shuvomoy Das, et al.
Published: (2020)
by: Gupta, Shuvomoy Das, et al.
Published: (2020)
Nonlinear conjugate gradient method for vector optimization on Riemannian manifolds with retraction and vector transport
by: Chen, Kangming, et al.
Published: (2023)
by: Chen, Kangming, et al.
Published: (2023)
Energy-optimal Timetable Design for Sustainable Metro Railway Networks
by: Gupta, Shuvomoy Das, et al.
Published: (2023)
by: Gupta, Shuvomoy Das, et al.
Published: (2023)
Almost sure convergence rates of stochastic gradient methods under gradient domination
by: Weissmann, Simon, et al.
Published: (2024)
by: Weissmann, Simon, et al.
Published: (2024)
An analytic framework for the multiplicative best-worst method
by: Ratandhara, Harshit, et al.
Published: (2023)
by: Ratandhara, Harshit, et al.
Published: (2023)
Non-linear in-band interference cancellation on base of conjugate gradients method
by: Degtyarev, Alexander, et al.
Published: (2026)
by: Degtyarev, Alexander, et al.
Published: (2026)
On the convergence analysis of the decentralized projected gradient descent method
by: Choi, Woocheol, et al.
Published: (2023)
by: Choi, Woocheol, et al.
Published: (2023)
A unified framework for inexact adaptive stepsizes in the gradient methods, the conjugate gradient methods and the quasi-Newton methods for strictly convex quadratic optimization
by: Liu, Zexian
Published: (2026)
by: Liu, Zexian
Published: (2026)
On the convergence of conditional gradient method for unbounded multiobjective optimization problems
by: Chen, Wang, et al.
Published: (2024)
by: Chen, Wang, et al.
Published: (2024)
Linear programming sensitivity measured by the optimal value worst-case analysis
by: Hladík, Milan
Published: (2023)
by: Hladík, Milan
Published: (2023)
About some works of Boris Polyak on convergence of gradient methods and their development
by: Ablaev, Seydamet, et al.
Published: (2023)
by: Ablaev, Seydamet, et al.
Published: (2023)
Provable non-accelerations of the heavy-ball method
by: Goujaud, Baptiste, et al.
Published: (2023)
by: Goujaud, Baptiste, et al.
Published: (2023)
Nonlinear conjugate gradient for smooth convex functions
by: Karimi, Sahar, et al.
Published: (2021)
by: Karimi, Sahar, et al.
Published: (2021)
Learning rate adaptive stochastic gradient descent optimization methods: numerical simulations for deep learning methods for partial differential equations and convergence analyses
by: Dereich, Steffen, et al.
Published: (2024)
by: Dereich, Steffen, et al.
Published: (2024)
A self-adaptive subgradient extragradient method with conjugate gradient-type direction for pseudomonotone variational inequalities
by: Arzuka, Ibrahim, et al.
Published: (2025)
by: Arzuka, Ibrahim, et al.
Published: (2025)
Effective rates for continuous-time quasi-Fejér monotone dynamical systems
by: Freund, Anton, et al.
Published: (2026)
by: Freund, Anton, et al.
Published: (2026)
Two-norm discrepancy and convergence of the stochastic gradient method with application to shape optimization
by: Dambrine, Marc, et al.
Published: (2024)
by: Dambrine, Marc, et al.
Published: (2024)
Learning complexity of gradient descent and conjugate gradient algorithms
by: Jiao, Xianqi, et al.
Published: (2024)
by: Jiao, Xianqi, et al.
Published: (2024)
A modified Polak-Ribiere-Polyak type conjugate gradient method with two stepsize strategies for vector optimization
by: Bai, Yushan, et al.
Published: (2024)
by: Bai, Yushan, et al.
Published: (2024)
Worst-case convergence analysis of relatively inexact gradient descent on smooth convex functions
by: Vernimmen, Pierre, et al.
Published: (2025)
by: Vernimmen, Pierre, et al.
Published: (2025)
Tight analyses of first-order methods with error feedback
by: Thomsen, Daniel Berg, et al.
Published: (2025)
by: Thomsen, Daniel Berg, et al.
Published: (2025)
Neural incomplete factorization: learning preconditioners for the conjugate gradient method
by: Häusner, Paul, et al.
Published: (2023)
by: Häusner, Paul, et al.
Published: (2023)
Taxicab distance based best-worst method for multi-criteria decision-making: An analytical approach
by: Ratandhara, Harshit, et al.
Published: (2024)
by: Ratandhara, Harshit, et al.
Published: (2024)
Local linear convergence of gradient methods for overparameterized Gaussian mixtures
by: Wang, Jingxing, et al.
Published: (2026)
by: Wang, Jingxing, et al.
Published: (2026)
Proximal gradient-type method with generalized distance and convergence analysis without global descent lemma
by: Yagishita, Shotaro, et al.
Published: (2025)
by: Yagishita, Shotaro, et al.
Published: (2025)
Automated tight Lyapunov analysis for first-order methods
by: Upadhyaya, Manu, et al.
Published: (2023)
by: Upadhyaya, Manu, et al.
Published: (2023)
Adaptive first-order methods with enhanced worst-case rates
by: Florea, Mihai I.
Published: (2024)
by: Florea, Mihai I.
Published: (2024)
On the Relation Between LP Sharpness and Limiting Error Ratio and Complexity Implications for Restarted PDHG
by: Xiong, Zikai, et al.
Published: (2023)
by: Xiong, Zikai, et al.
Published: (2023)
Computational Guarantees for Restarted PDHG for LP based on "Limiting Error Ratios" and LP Sharpness
by: Xiong, Zikai, et al.
Published: (2023)
by: Xiong, Zikai, et al.
Published: (2023)
The Role of Level-Set Geometry on the Performance of PDHG for Conic Linear Optimization
by: Xiong, Zikai, et al.
Published: (2024)
by: Xiong, Zikai, et al.
Published: (2024)
Slow convergence of the moment-SOS hierarchy for an elementary polynomial optimization problem
by: Henrion, Didier, et al.
Published: (2024)
by: Henrion, Didier, et al.
Published: (2024)
Minimum cost network flow with interval capacities: The worst-case scenario
by: Rada, Miroslav, et al.
Published: (2026)
by: Rada, Miroslav, et al.
Published: (2026)
Similar Items
-
The AutoLyap software suite for computer-assisted Lyapunov analyses of first-order methods
by: Upadhyaya, Manu, et al.
Published: (2025) -
PEPit: computer-assisted worst-case analyses of first-order optimization methods in Python
by: Goujaud, Baptiste, et al.
Published: (2022) -
Exact worst-case convergence rates for Douglas--Rachford and Davis--Yin splitting methods
by: Nguyen, Edward Duc Hien, et al.
Published: (2025) -
Exact worst-case convergence rates of gradient descent: a complete analysis for all constant stepsizes over nonconvex and convex functions
by: Rotaru, Teodor, et al.
Published: (2024) -
Computer-Assisted Design of Accelerated Composite Optimization Methods: OptISTA
by: Jang, Uijeong, et al.
Published: (2023)